Language

Seaborn

Source: 10-Data Analysis With Python/10.6-seaborn.ipynb

Start here — no coding background needed

What you will learn

Prettier statistical charts built on matplotlib.

In simple words

Seaborn makes beautiful plots with less code — use after pandas basics.

Spreadsheet-style work with code — for data jobs. Beginners: read concepts, run small examples.

Easy example — try this first

Easy example — run this first. Change values and press Run again.

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference notes (from full bootcamp)

Optional — deeper detail for when you are ready

Data Visualization With Seaborn

Seaborn is a Python visualization library based on Matplotlib that provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps in creating complex visualizations with just a few lines of code. In this lesson, we will cover the basics of Seaborn, including creating various types of plots and customizing them.

Example HCL

!pip install seaborn

Browser practice only — full example needs Python on your computer (files, Flask, threads, etc.).

Reference example

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference example

Output

Expected (from notebook):
     total_bill   tip     sex smoker   day    time  size
0         16.99  1.01  Female     No   Sun  Dinner     2
1         10.34  1.66    Male     No   Sun  Dinner     3
2         21.01  3.50    Male     No   Sun  Dinner     3
3         23.68  3.31    Male     No   Sun  Dinner     2
4         24.59  3.61  Female     No   Sun  Dinner     4
..          ...   ...     ...    ...   ...     ...   ...
239       29.03  5.92    Male     No   Sat  Dinner     3
240       27.18  2.00  Female    Yes   Sat  Dinner     2
241       22.67  2.00    Male    Yes   Sat  Dinner     2
242       17.82  1.75    Male     No   Sat  Dinner     2
243       18.78  3.00  Female     No  Thur  Dinner     2

[244 rows x 7 columns]

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Example HCL

##create a scatter plot
import matplotlib.pyplot as plt

sns.scatterplot(x='total_bill',y='tip',data=tips)
plt.title("Scatter Plot of Total Bill vs Tip")
plt.show()

Browser practice only — full example needs Python on your computer (files, Flask, threads, etc.).

Example HCL

## Line Plot

sns.lineplot(x='size',y='total_bill',data=tips)
plt.title("Line Plot of Total bill by size")
plt.show()

Browser practice only — full example needs Python on your computer (files, Flask, threads, etc.).

Example HCL

## Categorical Plots
## BAr Plot
sns.barplot(x='day',y='total_bill',data=tips)
plt.title('Bar Plot of Total Bill By Day')
plt.show()

Browser practice only — full example needs Python on your computer (files, Flask, threads, etc.).

Reference example

Output

Expected (from notebook):
<Axes: xlabel='day', ylabel='total_bill'>

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference example

Output

Expected (from notebook):
<Axes: xlabel='day', ylabel='total_bill'>

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference example

Output

Expected (from notebook):
<Axes: xlabel='total_bill', ylabel='Count'>

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference example

Output

Expected (from notebook):
<Axes: xlabel='total_bill', ylabel='Density'>

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference example

Output

Expected (from notebook):
<seaborn.axisgrid.PairGrid at 0x27547277770>

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference example

Output

Expected (from notebook):
     total_bill   tip     sex smoker   day    time  size
0         16.99  1.01  Female     No   Sun  Dinner     2
1         10.34  1.66    Male     No   Sun  Dinner     3
2         21.01  3.50    Male     No   Sun  Dinner     3
3         23.68  3.31    Male     No   Sun  Dinner     2
4         24.59  3.61  Female     No   Sun  Dinner     4
..          ...   ...     ...    ...   ...     ...   ...
239       29.03  5.92    Male     No   Sat  Dinner     3
240       27.18  2.00  Female    Yes   Sat  Dinner     2
241       22.67  2.00    Male    Yes   Sat  Dinner     2
242       17.82  1.75    Male     No   Sat  Dinner     2
243       18.78  3.00  Female     No  Thur  Dinner     2

[244 rows x 7 columns]

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference example

Output

Expected (from notebook):
            total_bill       tip      size
total_bill    1.000000  0.675734  0.598315
tip           0.675734  1.000000  0.489299
size          0.598315  0.489299  1.000000

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Reference example

Output

Expected (from notebook):
<Axes: >

Runs in your browser via Pyodide — no server. First run may take a few seconds.

Example HCL

import pandas as pd
sales_df=pd.read_csv('sales_data.csv')
sales_df.head()

Browser practice only — full example needs Python on your computer (files, Flask, threads, etc.).

Example HCL

## Plot total sales by product
plt.figure(figsize=(10,6))
sns.barplot(x='Product Category',y="Total Revenue",data=sales_df,estimator=sum)
plt.title('Total Sales by Product')
plt.xlabel('Product')
plt.ylabel('Total Sales')
plt.show()

Browser practice only — full example needs Python on your computer (files, Flask, threads, etc.).

Example HCL

## Plot total sales by Region
plt.figure(figsize=(10,6))
sns.barplot(x='Region',y="Total Revenue",data=sales_df,estimator=sum)
plt.title('Total Sales by Region')
plt.xlabel('Region')
plt.ylabel('Total Sales')
plt.show()

Browser practice only — full example needs Python on your computer (files, Flask, threads, etc.).

Practice test — try yourself

Write code, press Check. Wrong answer shows the correct code to copy & run.

You learned "Seaborn". Use print() to show: Done: Seaborn

Hint: Use one print() with the exact text.